From temblor : “Luzon in the Philippines sees sixth strong earthquake in five months”


From temblor

December 21, 2021

By Mario Aurelio, Director of the The University of the Philippines [Pamantasan ng Pilipinas or Unibersidad ng Pilipinas](PH) National Institute of Geological Sciences Sandra Donna Catugas, Structural Geology and Tectonics Laboratory at the University of Philippines National Institute of Geological Sciences
John Agustin Escudero, Structural Geology and Tectonics Laboratory at the University of Philippines National Institute of Geological Sciences
Alfredo Mahar Francisco Lagmay, Executive Director, University of the Philippines Resilience Institute-Nationwide Operational Assessment of Hazards Center (@nababaha)
Giovanni A. Tapang, Dean of the University of the Philippines-Diliman College of Science

On December 13, 2021, at 5:12 p.m. local time, the Batangas region in southern Luzon, Philippines, was hit by the fifth earthquake with a magnitude greater than 5.0 since a magnitude-6.6 tremor on July 24, 2021 (Aurelio et al., 2021a; 2021b; 2021c). Prior to this, four earthquakes with magnitude-5.8 (July 24 and August 13), 5.7 (September 27) and 5.2 (October 7) struck within a radius of 20 miles (30 kilometers) of the first July 24 event. This recurrence interval — an average of more than one strong earthquake every month — is too short to be neglected. This is either an unusually vigorous aftershock sequence, or an event comparable to a seismic swarm.

Area of stress increase

Using the fault responsible for generating the magnitude-6.6 earthquake of July 24, as the source fault, Coulomb stress transfer modeling indicates that the magnitude-5.5 tremor of December 13 falls within the lobe of increased stress when used as the receiver fault (Fig. 1). The 65-mile (104-kilometer) depth of the December tremor also plots approximately along the same fault plane, but four miles (seven kilometers) shallower than the July 24 event. These observations suggest that the first earthquake likely triggered the second.

Figure 1. Seismotectonics of six moderate magnitude, thrust-mechanism earthquakes (shown by beachballs) occurring in the same region in Batangas, southern Luzon, Philippines, within a period of five months (July 24 to December 13, 2021). Result of Coulomb stress change modeling shown. July 24 magnitude-6.6 as source; December 13 magnitude-5.5 as receiver. References: Jarvis et al., 2008 for SRTM topography; Weatherall et al., 2020 for bathymetry; Toda et al., 2011 for Coulomb stress transfer modeling; PHIVOLCS for earthquake data. GMT (Wessel and Smith, 1995) was used to generate the map. See text for more discussion. Credit: Aurelio, Catugas, Escudero, Lagmay,Tapang.

The same triggering mechanism can explain three of the other recent magnitude-5.0 and larger events when each is used as the receiver fault (Aurelio et al., 2021a; 2021b), except for the magnitude-5.7 quake of September 27, which occurred in a zone of decreased stress (Aurelio et al., 2021c).

However, when Coulomb stress transfer modeling considers an optimally-oriented receiver fault — assumed to be aligned with the stress field, thus promoting failure — all five earthquakes that succeeded the July 24 magnitude-6.6 earthquake fall within the lobe of increased stress at 65 miles (104 kilometers) depth (Fig. 2). The hypocenters — the locations on the fault where each earthquake nucleated — cluster within the calculated region of increased stress, which suggests triggering of all five quakes by the magnitude-6.6 July 24 event.

Figure 2. Seismotectonics of six moderate magnitude, thrust-mechanism earthquakes (shown by beachballs) occurring in the same region in Batangas, southern Luzon, Philippines, within a period of five months (July 24 to December 13, 2021). Result of Coulomb stress change modeling shown. July 24 magnitude-6.6 as source, with optimally-oriented fault as receiver. References: Jarvis et al., 2008 for SRTM topography; Weatherall et al., 2020 for bathymetry; Toda et al., 2011 for Coulomb stress transfer modeling; PHIVOLCS for earthquake data. GMT (Wessel and Smith, 1995) was used to generate the map. See text for more discussion. Credit: Aurelio, Catugas, Escudero, Lagmay,Tapang.

Cause for concern?

Based on the data collected during the last decade (Aurelio et al., 2021b), an average of 2.5 events larger than magnitude-5.0 strike per year within 50 kilometers of the July 24 magnitude-6.6 event. The recent spate of moderate quakes — each separated by less than a month — far exceeds this average and suggests that this is an evolving sequence.

Could these six moderate magnitude earthquakes occurring over a short period of time indicate that stresses are being released rapidly? Or could these be lower-magnitude foreshocks of a larger event that has yet to strike? The latter is a possibility and should serve as a reminder to the 25 million inhabitants of Metro Manila and surrounding provinces that this region is vulnerable to a large earthquake. Preparedness and readiness are vital.

Low-cost seismology studies

The December 13 tremor was recorded by low-cost seismometers partly belonging to Public Seismic Network that is currently being established by the College of Science of the University of the Philippines-Diliman (UP Diliman) in Quezon City (Fig. 3). These low-cost seismometers, developed by Raspberry Shake, have been tried and tested both in the laboratory (Anthony et al., 2019) and in the field (Manconi et al., 2018; Winter et al., 2021; Holmgren, 2021).

Figure 3. Earthquake information generated by a Raspberry Shake station located nearest to the Public Seismic Network hub located inside the University of the Philippines-Diliman campus in Quezon City. The figure is a screenshot from the mobile phone app showing on the: upper panel – the date and time (local) of the seismic event, earthquake parameters (magnitude-5.5 and focal depth of 157 kilometers), station ID: R5160, map showing the locations of the Raspberry Shake seismic station and the epicenter and, station-to-epicenter distance in kilometers; middle panel – the waveform of the earthquake, clearly delineating the first P and S waves; lower panel – wave frequency distribution as a function of time. Credit: Aurelio, Catugas, Escudero, Lagmay, Tapang

The earthquake parameters for December’s quake, generated by the UP Diliman-based network, include a calculated magnitude of 5.5, which compares well with magnitudes calculated by established international seismological observatories such as The Geological Survey (US) – National Earthquake Information Center (USGS-NEIC), GEOFON German Research Center for Geosciences (GEOFON-GFZ, Potsdam, Germany) and PHIVOLCS (Philippines). The low-cost, Raspberry Shake-derived earthquake depth of 98 miles (157 kilometers) is close to that computed by USGS-NEIC, but varies significantly from GEOFON-GFZ (69 miles/111 kilometers) and PHIVOLCS (64 miles/104 kilometers) estimates.

Currently, most of these low-cost seismometers are owned and operated by ordinary citizens on their private properties. Though the stations are still scarce, there are good indications that more citizens are interested in setting up their own stations to join the UP Diliman-based network. Efforts are underway to find funds for more seismometers to deploy in schools throughout the country, with the aims of expanding the network and serving as a learning and teaching platform for students interested in earthquake studies.

Meanwhile, at the UP National Institute of Physics (UP-NIP), a group of scientists from the institutes’ Instrumentation Physics Laboratory (ILP), is developing a low-cost seismic network consisting of accelerometers manufactured from commercially available components (Fig. 4). Each accelerometer costs less than $200 USD to manufacture. This network is part of a study to understand how shaking decays with distance from the source and how it is influenced by the nature of the ground underneath — called a ground attenuation relationship. Current attenuation relationships used in the country come from outside the Philippines, including experimental results from artificially induced, low-magnitude earthquakes, and data gathered directly from natural earthquakes.

Figure 4. Custom-made ground motion sensor (accelerometer) fabricated at the Instrumentation Physics Laboratory (IPL) of the University of the Philippines National Institute of Physics. The sensor contains the following components: (Left photo) (1) digital accelerometer; (2) development board containing the microcontroller, SD card module, and antenna for Long Range (LoRa) reception capabilities; (3) power section of board; (4) GPS module; (5) Real Time Clock (RTC) module; (6) antenna; (7) storage module; (8) power switch, (9) connection to the battery (not seen in picture) secured at the bottom of the container. (Right photo) Sensor assembled inside a closed, laser-cut acrylic sheet, with the electronic parts secured inside, connected to a pipe that serves as an extended antenna. The acrylic box is equipped with a level (button on top) to ensure horizontality of the base of the sensor. Credit: Aurelio (ongoing).

These complementary efforts to establish low-cost seismological observatories serve two purposes. The Raspberry Shake network promotes citizen science. The second effort led by scientists helps Philippine researchers conduct innovative but inexpensive earthquake research. Both efforts hold promise in contributing to hazard resilience in an earthquake-prone country that often lacks scientific research funds.


Anthony, R.E., Ringler, A., Wilson D.C., and Wolin, E. (2019). Do Low-Cost Seismographs Perform Well Enough for Your Network? An Overview of Laboratory Tests and Field Observations of the OSOP Raspberry Shake 4D. Seismological Research Letters. 90 (1): 219-228.

Aurelio, M. (ongoing). Project Leader: Establishing a ground attenuation relation for the Philippines using artificial blasting methods. Project funded by the University of the Philippines – Office of the Vice-President for Academic Affairs (UP-OVPAA) under the Enhanced Creative Work Research Grant (ECWRG).

Aurelio, M., Lagmay, M., Escudero, J. A., and Catugas, S. (2021a). Latest Philippine earthquake reveals tectonic complexity, Temblor,

Aurelio, M., Lagmay, M., Escudero, J. A., and Catugas, S. (2021b). Philippine fault jolts Batangas again, with magnitude-5.8 quake, Temblor,

Aurelio, M., Lagmay, M., Escudero, J. A., and Catugas, S. (2021c). Magnitude-5.7 Batangas earthquake puzzles researchers, Temblor,

GEOFON German Research Center for Geosciences. Available at:

Holmgren, J.M and Werner, M. (2021). Raspberry Shake Instruments Provide Initial Ground‐Motion Assessment of the Induced Seismicity at the United Downs Deep Geothermal Power Project in Cornwall, United Kingdom. The Seismic Record 1 (1): 27–34.

Jarvis, A., H.I. Reuter, A. Nelson, E. Guevara (2008). Hole-filled SRTM for the globe Version 4, available from the CGIAR-CSI SRTM 90m Database (

Manconi, A., Coviello, V. and Galletti, M. (2018). Short Communication: Monitoring Rockfall with the Raspberry Shake. Earth Surface Dynamics 6(4): 1219-1227.

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Philippine Institute of Volcanology and Seismology (PHIVOLCS). Available at:

Toda, Shinji, Stein, R.S., Sevilgen, Volkan, and Lin, J. (2011). Coulomb 3.3 Graphic-rich deformation and stress-change software for earthquake, tectonic, and volcano research and teaching—user guide: U.S. Geological Survey Open-File Report 2011–1060, 63 p., available at

United States Geological Survey – National Earthquake Information Center (USGS-NEIC). Available at:

Weatherall P., Tozer B., Arndt J.E., Bazhenova E., Bringensparr C., Castro C.F., Dorschel B., Ferrini V., Hehemann L., Jakobsson M., Johnson P., Ketter T., Mackay K., Martin T.V., Mayer L.A., McMichael-Phillips J., Mohammad R., Nitsche F.O., Sandwell D.T., Snaith H., Viquerat S. (2020). The GEBCO_2020 Grid – a continuous terrain model of the global oceans and land. British Oceanographic Data Centre, National Oceanography Centre, NERC, UK. doi:10.5285/a29c5465-b138-234d-e053-6c86abc040b9

Wessel, P. and Smith, W.H.F., (1995). New version of the Generic Mapping Tools released. EOS Trans. Am. Geophys. Union 76, 329.

Winter, K., Lombardi, D. Diaz-Moreno A., and Bainbridge, R. (2021). Monitoring Icequakes in East Antarctica with the Raspberry Shake. Seismological Research Letters. Doi:

See the full article here .


Please help promote STEM in your local schools.

Stem Education Coalition


Earthquake Alert


Earthquake Alert

Earthquake Network project Earthquake Network is a research project which aims at developing and maintaining a crowdsourced smartphone-based earthquake warning system at a global level. Smartphones made available by the population are used to detect the earthquake waves using the on-board accelerometers. When an earthquake is detected, an earthquake warning is issued in order to alert the population not yet reached by the damaging waves of the earthquake.

The project started on January 1, 2013 with the release of the homonymous Android application Earthquake Network. The author of the research project and developer of the smartphone application is Francesco Finazzi of the University of Bergamo, Italy.

Get the app in the Google Play store.

Smartphone network spatial distribution (green and red dots) on December 4, 2015

Meet The Quake-Catcher Network

QCN bloc

Quake-Catcher Network

The Quake-Catcher Network is a collaborative initiative for developing the world’s largest, low-cost strong-motion seismic network by utilizing sensors in and attached to internet-connected computers. With your help, the Quake-Catcher Network can provide better understanding of earthquakes, give early warning to schools, emergency response systems, and others. The Quake-Catcher Network also provides educational software designed to help teach about earthquakes and earthquake hazards.

After almost eight years at Stanford, and a year at CalTech, the QCN project is moving to the University of Southern California Dept. of Earth Sciences. QCN will be sponsored by the Incorporated Research Institutions for Seismology (IRIS) and the Southern California Earthquake Center (SCEC).

The Quake-Catcher Network is a distributed computing network that links volunteer hosted computers into a real-time motion sensing network. QCN is one of many scientific computing projects that runs on the world-renowned distributed computing platform Berkeley Open Infrastructure for Network Computing (BOINC).

The volunteer computers monitor vibrational sensors called MEMS accelerometers, and digitally transmit “triggers” to QCN’s servers whenever strong new motions are observed. QCN’s servers sift through these signals, and determine which ones represent earthquakes, and which ones represent cultural noise (like doors slamming, or trucks driving by).

There are two categories of sensors used by QCN: 1) internal mobile device sensors, and 2) external USB sensors.

Mobile Devices: MEMS sensors are often included in laptops, games, cell phones, and other electronic devices for hardware protection, navigation, and game control. When these devices are still and connected to QCN, QCN software monitors the internal accelerometer for strong new shaking. Unfortunately, these devices are rarely secured to the floor, so they may bounce around when a large earthquake occurs. While this is less than ideal for characterizing the regional ground shaking, many such sensors can still provide useful information about earthquake locations and magnitudes.

USB Sensors: MEMS sensors can be mounted to the floor and connected to a desktop computer via a USB cable. These sensors have several advantages over mobile device sensors. 1) By mounting them to the floor, they measure more reliable shaking than mobile devices. 2) These sensors typically have lower noise and better resolution of 3D motion. 3) Desktops are often left on and do not move. 4) The USB sensor is physically removed from the game, phone, or laptop, so human interaction with the device doesn’t reduce the sensors’ performance. 5) USB sensors can be aligned to North, so we know what direction the horizontal “X” and “Y” axes correspond to.

If you are a science teacher at a K-12 school, please apply for a free USB sensor and accompanying QCN software. QCN has been able to purchase sensors to donate to schools in need. If you are interested in donating to the program or requesting a sensor, click here.

BOINC is a leader in the field(s) of Distributed Computing, Grid Computing and Citizen Cyberscience.BOINC is more properly the Berkeley Open Infrastructure for Network Computing, developed at UC Berkeley.

Earthquake safety is a responsibility shared by billions worldwide. The Quake-Catcher Network (QCN) provides software so that individuals can join together to improve earthquake monitoring, earthquake awareness, and the science of earthquakes. The Quake-Catcher Network (QCN) links existing networked laptops and desktops in hopes to form the worlds largest strong-motion seismic network.

Below, the QCN Quake Catcher Network map
QCN Quake Catcher Network map

ShakeAlert: An Earthquake Early Warning System for the West Coast of the United States

The U. S. Geological Survey (USGS) along with a coalition of State and university partners is developing and testing an earthquake early warning (EEW) system called ShakeAlert for the west coast of the United States. Long term funding must be secured before the system can begin sending general public notifications, however, some limited pilot projects are active and more are being developed. The USGS has set the goal of beginning limited public notifications in 2018.

Watch a video describing how ShakeAlert works in English or Spanish.

The primary project partners include:

United States Geological Survey
California Governor’s Office of Emergency Services (CalOES)
California Geological Survey
California Institute of Technology
University of California Berkeley
University of Washington
University of Oregon
Gordon and Betty Moore Foundation

The Earthquake Threat

Earthquakes pose a national challenge because more than 143 million Americans live in areas of significant seismic risk across 39 states. Most of our Nation’s earthquake risk is concentrated on the West Coast of the United States. The Federal Emergency Management Agency (FEMA) has estimated the average annualized loss from earthquakes, nationwide, to be $5.3 billion, with 77 percent of that figure ($4.1 billion) coming from California, Washington, and Oregon, and 66 percent ($3.5 billion) from California alone. In the next 30 years, California has a 99.7 percent chance of a magnitude 6.7 or larger earthquake and the Pacific Northwest has a 10 percent chance of a magnitude 8 to 9 megathrust earthquake on the Cascadia subduction zone.

Part of the Solution

Today, the technology exists to detect earthquakes, so quickly, that an alert can reach some areas before strong shaking arrives. The purpose of the ShakeAlert system is to identify and characterize an earthquake a few seconds after it begins, calculate the likely intensity of ground shaking that will result, and deliver warnings to people and infrastructure in harm’s way. This can be done by detecting the first energy to radiate from an earthquake, the P-wave energy, which rarely causes damage. Using P-wave information, we first estimate the location and the magnitude of the earthquake. Then, the anticipated ground shaking across the region to be affected is estimated and a warning is provided to local populations. The method can provide warning before the S-wave arrives, bringing the strong shaking that usually causes most of the damage.

Studies of earthquake early warning methods in California have shown that the warning time would range from a few seconds to a few tens of seconds. ShakeAlert can give enough time to slow trains and taxiing planes, to prevent cars from entering bridges and tunnels, to move away from dangerous machines or chemicals in work environments and to take cover under a desk, or to automatically shut down and isolate industrial systems. Taking such actions before shaking starts can reduce damage and casualties during an earthquake. It can also prevent cascading failures in the aftermath of an event. For example, isolating utilities before shaking starts can reduce the number of fire initiations.

System Goal

The USGS will issue public warnings of potentially damaging earthquakes and provide warning parameter data to government agencies and private users on a region-by-region basis, as soon as the ShakeAlert system, its products, and its parametric data meet minimum quality and reliability standards in those geographic regions. The USGS has set the goal of beginning limited public notifications in 2018. Product availability will expand geographically via ANSS regional seismic networks, such that ShakeAlert products and warnings become available for all regions with dense seismic instrumentation.

Current Status

The West Coast ShakeAlert system is being developed by expanding and upgrading the infrastructure of regional seismic networks that are part of the Advanced National Seismic System (ANSS); the California Integrated Seismic Network (CISN) is made up of the Southern California Seismic Network, SCSN) and the Northern California Seismic System, NCSS and the Pacific Northwest Seismic Network (PNSN). This enables the USGS and ANSS to leverage their substantial investment in sensor networks, data telemetry systems, data processing centers, and software for earthquake monitoring activities residing in these network centers. The ShakeAlert system has been sending live alerts to “beta” users in California since January of 2012 and in the Pacific Northwest since February of 2015.

In February of 2016 the USGS, along with its partners, rolled-out the next-generation ShakeAlert early warning test system in California joined by Oregon and Washington in April 2017. This West Coast-wide “production prototype” has been designed for redundant, reliable operations. The system includes geographically distributed servers, and allows for automatic fail-over if connection is lost.

This next-generation system will not yet support public warnings but does allow selected early adopters to develop and deploy pilot implementations that take protective actions triggered by the ShakeAlert notifications in areas with sufficient sensor coverage.


The USGS will develop and operate the ShakeAlert system, and issue public notifications under collaborative authorities with FEMA, as part of the National Earthquake Hazard Reduction Program, as enacted by the Earthquake Hazards Reduction Act of 1977, 42 U.S.C. §§ 7704 SEC. 2.

For More Information

Robert de Groot, ShakeAlert National Coordinator for Communication, Education, and Outreach

Learn more about EEW Research

ShakeAlert Fact Sheet

ShakeAlert Implementation Plan



About Early Warning Labs, LLC

Early Warning Labs, LLC (EWL) is an Earthquake Early Warning technology developer and integrator located in Santa Monica, CA. EWL is partnered with industry leading GIS provider ESRI, Inc. and is collaborating with the US Government and university partners.

EWL is investing millions of dollars over the next 36 months to complete the final integration and delivery of Earthquake Early Warning to individual consumers, government entities, and commercial users.

EWL’s mission is to improve, expand, and lower the costs of the existing earthquake early warning systems.

EWL is developing a robust cloud server environment to handle low-cost mass distribution of these warnings. In addition, Early Warning Labs is researching and developing automated response standards and systems that allow public and private users to take pre-defined automated actions to protect lives and assets.

EWL has an existing beta R&D test system installed at one of the largest studios in Southern California. The goal of this system is to stress test EWL’s hardware, software, and alert signals while improving latency and reliability.

Earthquake Early Warning Introduction

The United States Geological Survey (USGS), in collaboration with state agencies, university partners, and private industry, is developing an earthquake early warning system (EEW) for the West Coast of the United States called ShakeAlert. The USGS Earthquake Hazards Program aims to mitigate earthquake losses in the United States. Citizens, first responders, and engineers rely on the USGS for accurate and timely information about where earthquakes occur, the ground shaking intensity in different locations, and the likelihood is of future significant ground shaking.

The ShakeAlert Earthquake Early Warning System recently entered its first phase of operations. The USGS working in partnership with the California Governor’s Office of Emergency Services (Cal OES) is now allowing for the testing of public alerting via apps, Wireless Emergency Alerts, and by other means throughout California.

ShakeAlert partners in Oregon and Washington are working with the USGS to test public alerting in those states sometime in 2020.

ShakeAlert has demonstrated the feasibility of earthquake early warning, from event detection to producing USGS issued ShakeAlerts ® and will continue to undergo testing and will improve over time. In particular, robust and reliable alert delivery pathways for automated actions are currently being developed and implemented by private industry partners for use in California, Oregon, and Washington.

Earthquake Early Warning Background

The objective of an earthquake early warning system is to rapidly detect the initiation of an earthquake, estimate the level of ground shaking intensity to be expected, and issue a warning before significant ground shaking starts. A network of seismic sensors detects the first energy to radiate from an earthquake, the P-wave energy, and the location and the magnitude of the earthquake is rapidly determined. Then, the anticipated ground shaking across the region to be affected is estimated. The system can provide warning before the S-wave arrives, which brings the strong shaking that usually causes most of the damage. Warnings will be distributed to local and state public emergency response officials, critical infrastructure, private businesses, and the public. EEW systems have been successfully implemented in Japan, Taiwan, Mexico, and other nations with varying degrees of sophistication and coverage.

Earthquake early warning can provide enough time to:

Instruct students and employees to take a protective action such as Drop, Cover, and Hold On
Initiate mass notification procedures
Open fire-house doors and notify local first responders
Slow and stop trains and taxiing planes
Install measures to prevent/limit additional cars from going on bridges, entering tunnels, and being on freeway overpasses before the shaking starts
Move people away from dangerous machines or chemicals in work environments
Shut down gas lines, water treatment plants, or nuclear reactors
Automatically shut down and isolate industrial systems

However, earthquake warning notifications must be transmitted without requiring human review and response action must be automated, as the total warning times are short depending on geographic distance and varying soil densities from the epicenter.